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<a href="#pub-types">Public 类型</a> &#124;
<a href="#pub-methods">Public 成员函数</a> &#124;
<a href="classpcl_1_1_sample_consensus_model_normal_plane-members.html">所有成员列表</a>  </div>
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<div class="title">pcl::SampleConsensusModelNormalPlane&lt; PointT, PointNT &gt; 模板类 参考</div>  </div>
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<p><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html" title="SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface no...">SampleConsensusModelNormalPlane</a> defines a model for 3D plane segmentation using additional surface normal constraints. Basically this means that checking for inliers will not only involve a "distance to
model" criterion, but also an additional "maximum angular deviation" between the plane's normal and the inlier points normals.  
 <a href="classpcl_1_1_sample_consensus_model_normal_plane.html#details">更多...</a></p>

<p><code>#include &lt;<a class="el" href="sac__model__normal__plane_8h_source.html">sac_model_normal_plane.h</a>&gt;</code></p>
<div class="dynheader">
类 pcl::SampleConsensusModelNormalPlane&lt; PointT, PointNT &gt; 继承关系图:</div>
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 <div class="center">
  <img src="classpcl_1_1_sample_consensus_model_normal_plane.png" usemap="#pcl::SampleConsensusModelNormalPlane_3C_20PointT_2C_20PointNT_20_3E_map" alt=""/>
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<area href="classpcl_1_1_sample_consensus_model_normal_parallel_plane.html" title="SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional su..." alt="pcl::SampleConsensusModelNormalParallelPlane&lt; PointT, PointNT &gt;" shape="rect" coords="205,168,605,192"/>
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<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public 类型</h2></td></tr>
<tr class="memitem:a63dedc5ca98e6fc974da667199644415"><td class="memItemLeft" align="right" valign="top"><a id="a63dedc5ca98e6fc974da667199644415"></a>
typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::<a class="el" href="classpcl_1_1_point_cloud.html">PointCloud</a>&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
<tr class="separator:a63dedc5ca98e6fc974da667199644415"><td class="memSeparator" colspan="2">&#160;</td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">SampleConsensusModelFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::PointCloudNPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">SampleConsensusModelFromNormals</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNConstPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">SampleConsensusModelNormalPlane</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_sample_consensus_model_plane"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_sample_consensus_model_plane')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model_plane.html">pcl::SampleConsensusModelPlane&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a0bb46c0277fd4554dec5a2b43ea9200c inherit pub_types_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top"><a id="a0bb46c0277fd4554dec5a2b43ea9200c"></a>
typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::<a class="el" href="classpcl_1_1_point_cloud.html">PointCloud</a>&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::PointCloudPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_sample_consensus_model_plane.html">SampleConsensusModelPlane</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_sample_consensus_model"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_sample_consensus_model')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model.html">pcl::SampleConsensusModel&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a70b51e8d9f8526c1d2dc69ce68d9269e inherit pub_types_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a70b51e8d9f8526c1d2dc69ce68d9269e"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloud</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudConstPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudPtr</b></td></tr>
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typedef <a class="el" href="classpcl_1_1search_1_1_search.html">pcl::search::Search</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &gt;::Ptr&#160;</td><td class="memItemRight" valign="bottom"><b>SearchPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1_sample_consensus_model.html">SampleConsensusModel</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
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<tr class="inherit_header pub_types_classpcl_1_1_sample_consensus_model_from_normals"><td colspan="2" onclick="javascript:toggleInherit('pub_types_classpcl_1_1_sample_consensus_model_from_normals')"><img src="closed.png" alt="-"/>&#160;Public 类型 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">pcl::SampleConsensusModelFromNormals&lt; PointT, PointNT &gt;</a></td></tr>
<tr class="memitem:af2f51a94d8d72e9886ec81ced2c0e409 inherit pub_types_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="af2f51a94d8d72e9886ec81ced2c0e409"></a>
typedef <a class="el" href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a>&lt; PointNT &gt;::ConstPtr&#160;</td><td class="memItemRight" valign="bottom"><b>PointCloudNConstPtr</b></td></tr>
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typedef boost::shared_ptr&lt; <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">SampleConsensusModelFromNormals</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>Ptr</b></td></tr>
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typedef boost::shared_ptr&lt; const <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">SampleConsensusModelFromNormals</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><b>ConstPtr</b></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public 成员函数</h2></td></tr>
<tr class="memitem:a6057b518b385f7cb814a21f0e624069d"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#a6057b518b385f7cb814a21f0e624069d">SampleConsensusModelNormalPlane</a> (const PointCloudConstPtr &amp;cloud, bool random=false)</td></tr>
<tr class="memdesc:a6057b518b385f7cb814a21f0e624069d"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html" title="SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface no...">SampleConsensusModelNormalPlane</a>.  <a href="classpcl_1_1_sample_consensus_model_normal_plane.html#a6057b518b385f7cb814a21f0e624069d">更多...</a><br /></td></tr>
<tr class="separator:a6057b518b385f7cb814a21f0e624069d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab86a5b9c29702bf097861986d9ea67bf"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#ab86a5b9c29702bf097861986d9ea67bf">SampleConsensusModelNormalPlane</a> (const PointCloudConstPtr &amp;cloud, const std::vector&lt; int &gt; &amp;indices, bool random=false)</td></tr>
<tr class="memdesc:ab86a5b9c29702bf097861986d9ea67bf"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html" title="SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface no...">SampleConsensusModelNormalPlane</a>.  <a href="classpcl_1_1_sample_consensus_model_normal_plane.html#ab86a5b9c29702bf097861986d9ea67bf">更多...</a><br /></td></tr>
<tr class="separator:ab86a5b9c29702bf097861986d9ea67bf"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a599399a6a03a7ddb4bb26bb304b8b871"><td class="memItemLeft" align="right" valign="top"><a id="a599399a6a03a7ddb4bb26bb304b8b871"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#a599399a6a03a7ddb4bb26bb304b8b871">~SampleConsensusModelNormalPlane</a> ()</td></tr>
<tr class="memdesc:a599399a6a03a7ddb4bb26bb304b8b871"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor <br /></td></tr>
<tr class="separator:a599399a6a03a7ddb4bb26bb304b8b871"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a63bbd86abcfc9a3ac2572d7d4566cd35"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#a63bbd86abcfc9a3ac2572d7d4566cd35">selectWithinDistance</a> (const Eigen::VectorXf &amp;model_coefficients, const double threshold, std::vector&lt; int &gt; &amp;inliers)</td></tr>
<tr class="memdesc:a63bbd86abcfc9a3ac2572d7d4566cd35"><td class="mdescLeft">&#160;</td><td class="mdescRight">Select all the points which respect the given model coefficients as inliers.  <a href="classpcl_1_1_sample_consensus_model_normal_plane.html#a63bbd86abcfc9a3ac2572d7d4566cd35">更多...</a><br /></td></tr>
<tr class="separator:a63bbd86abcfc9a3ac2572d7d4566cd35"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a97823e42845ee811261d929ecc272005"><td class="memItemLeft" align="right" valign="top">virtual int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#a97823e42845ee811261d929ecc272005">countWithinDistance</a> (const Eigen::VectorXf &amp;model_coefficients, const double threshold)</td></tr>
<tr class="memdesc:a97823e42845ee811261d929ecc272005"><td class="mdescLeft">&#160;</td><td class="mdescRight">Count all the points which respect the given model coefficients as inliers.  <a href="classpcl_1_1_sample_consensus_model_normal_plane.html#a97823e42845ee811261d929ecc272005">更多...</a><br /></td></tr>
<tr class="separator:a97823e42845ee811261d929ecc272005"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad084c665f423e894bd4531c02f38c5a0"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#ad084c665f423e894bd4531c02f38c5a0">getDistancesToModel</a> (const Eigen::VectorXf &amp;model_coefficients, std::vector&lt; double &gt; &amp;distances)</td></tr>
<tr class="memdesc:ad084c665f423e894bd4531c02f38c5a0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute all distances from the cloud data to a given plane model.  <a href="classpcl_1_1_sample_consensus_model_normal_plane.html#ad084c665f423e894bd4531c02f38c5a0">更多...</a><br /></td></tr>
<tr class="separator:ad084c665f423e894bd4531c02f38c5a0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a415ea4b0cd33afe4429a76e9208ee88e"><td class="memItemLeft" align="right" valign="top"><a id="a415ea4b0cd33afe4429a76e9208ee88e"></a>
pcl::SacModel&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html#a415ea4b0cd33afe4429a76e9208ee88e">getModelType</a> () const</td></tr>
<tr class="memdesc:a415ea4b0cd33afe4429a76e9208ee88e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return an unique id for this model (SACMODEL_NORMAL_PLANE). <br /></td></tr>
<tr class="separator:a415ea4b0cd33afe4429a76e9208ee88e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_sample_consensus_model_plane"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_sample_consensus_model_plane')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model_plane.html">pcl::SampleConsensusModelPlane&lt; PointT &gt;</a></td></tr>
<tr class="memitem:ac99bcc81fa7f1bb2490020ff3ac1aeb6 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#ac99bcc81fa7f1bb2490020ff3ac1aeb6">SampleConsensusModelPlane</a> (const PointCloudConstPtr &amp;cloud, bool random=false)</td></tr>
<tr class="memdesc:ac99bcc81fa7f1bb2490020ff3ac1aeb6 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_plane.html" title="SampleConsensusModelPlane defines a model for 3D plane segmentation. The model coefficients are defin...">SampleConsensusModelPlane</a>.  <a href="classpcl_1_1_sample_consensus_model_plane.html#ac99bcc81fa7f1bb2490020ff3ac1aeb6">更多...</a><br /></td></tr>
<tr class="separator:ac99bcc81fa7f1bb2490020ff3ac1aeb6 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adba03adf3afc5135b049cd4dae8fe3bb inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#adba03adf3afc5135b049cd4dae8fe3bb">SampleConsensusModelPlane</a> (const PointCloudConstPtr &amp;cloud, const std::vector&lt; int &gt; &amp;indices, bool random=false)</td></tr>
<tr class="memdesc:adba03adf3afc5135b049cd4dae8fe3bb inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_plane.html" title="SampleConsensusModelPlane defines a model for 3D plane segmentation. The model coefficients are defin...">SampleConsensusModelPlane</a>.  <a href="classpcl_1_1_sample_consensus_model_plane.html#adba03adf3afc5135b049cd4dae8fe3bb">更多...</a><br /></td></tr>
<tr class="separator:adba03adf3afc5135b049cd4dae8fe3bb inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afd2dec2c1f550eedba0ced17f4394e19 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top"><a id="afd2dec2c1f550eedba0ced17f4394e19"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#afd2dec2c1f550eedba0ced17f4394e19">~SampleConsensusModelPlane</a> ()</td></tr>
<tr class="memdesc:afd2dec2c1f550eedba0ced17f4394e19 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty destructor <br /></td></tr>
<tr class="separator:afd2dec2c1f550eedba0ced17f4394e19 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab8c1ca289b6b38d9e00395ced6004f6a inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#ab8c1ca289b6b38d9e00395ced6004f6a">computeModelCoefficients</a> (const std::vector&lt; int &gt; &amp;samples, Eigen::VectorXf &amp;model_coefficients)</td></tr>
<tr class="memdesc:ab8c1ca289b6b38d9e00395ced6004f6a inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check whether the given index samples can form a valid plane model, compute the model coefficients from these samples and store them internally in model_coefficients_. The plane coefficients are: a, b, c, d (ax+by+cz+d=0)  <a href="classpcl_1_1_sample_consensus_model_plane.html#ab8c1ca289b6b38d9e00395ced6004f6a">更多...</a><br /></td></tr>
<tr class="separator:ab8c1ca289b6b38d9e00395ced6004f6a inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a50387ca38d44d96d364cff901da7bd42 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#a50387ca38d44d96d364cff901da7bd42">getDistancesToModel</a> (const Eigen::VectorXf &amp;model_coefficients, std::vector&lt; double &gt; &amp;distances)</td></tr>
<tr class="memdesc:a50387ca38d44d96d364cff901da7bd42 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute all distances from the cloud data to a given plane model.  <a href="classpcl_1_1_sample_consensus_model_plane.html#a50387ca38d44d96d364cff901da7bd42">更多...</a><br /></td></tr>
<tr class="separator:a50387ca38d44d96d364cff901da7bd42 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aeb06aa4934ddf5ce6a5cd7220eb6c121 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#aeb06aa4934ddf5ce6a5cd7220eb6c121">selectWithinDistance</a> (const Eigen::VectorXf &amp;model_coefficients, const double threshold, std::vector&lt; int &gt; &amp;inliers)</td></tr>
<tr class="memdesc:aeb06aa4934ddf5ce6a5cd7220eb6c121 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Select all the points which respect the given model coefficients as inliers.  <a href="classpcl_1_1_sample_consensus_model_plane.html#aeb06aa4934ddf5ce6a5cd7220eb6c121">更多...</a><br /></td></tr>
<tr class="separator:aeb06aa4934ddf5ce6a5cd7220eb6c121 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7fe6c9952d5dae0d7366a2fe3be37dd9 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#a7fe6c9952d5dae0d7366a2fe3be37dd9">optimizeModelCoefficients</a> (const std::vector&lt; int &gt; &amp;inliers, const Eigen::VectorXf &amp;model_coefficients, Eigen::VectorXf &amp;optimized_coefficients)</td></tr>
<tr class="memdesc:a7fe6c9952d5dae0d7366a2fe3be37dd9 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Recompute the plane coefficients using the given inlier set and return them to the user.  <a href="classpcl_1_1_sample_consensus_model_plane.html#a7fe6c9952d5dae0d7366a2fe3be37dd9">更多...</a><br /></td></tr>
<tr class="separator:a7fe6c9952d5dae0d7366a2fe3be37dd9 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af440c5df78301786addbb085036aa447 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#af440c5df78301786addbb085036aa447">projectPoints</a> (const std::vector&lt; int &gt; &amp;inliers, const Eigen::VectorXf &amp;model_coefficients, <a class="el" href="classpcl_1_1_point_cloud.html">PointCloud</a> &amp;projected_points, bool copy_data_fields=true)</td></tr>
<tr class="memdesc:af440c5df78301786addbb085036aa447 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create a new point cloud with inliers projected onto the plane model.  <a href="classpcl_1_1_sample_consensus_model_plane.html#af440c5df78301786addbb085036aa447">更多...</a><br /></td></tr>
<tr class="separator:af440c5df78301786addbb085036aa447 inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34ab4d472c46cf75e3cf7b3bec4346bd inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#a34ab4d472c46cf75e3cf7b3bec4346bd">doSamplesVerifyModel</a> (const std::set&lt; int &gt; &amp;indices, const Eigen::VectorXf &amp;model_coefficients, const double threshold)</td></tr>
<tr class="memdesc:a34ab4d472c46cf75e3cf7b3bec4346bd inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Verify whether a subset of indices verifies the given plane model coefficients.  <a href="classpcl_1_1_sample_consensus_model_plane.html#a34ab4d472c46cf75e3cf7b3bec4346bd">更多...</a><br /></td></tr>
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<tr class="memitem:aec6058c4d1e3e467d17954557216c43e inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memItemLeft" align="right" valign="top"><a id="aec6058c4d1e3e467d17954557216c43e"></a>
pcl::SacModel&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#aec6058c4d1e3e467d17954557216c43e">getModelType</a> () const</td></tr>
<tr class="memdesc:aec6058c4d1e3e467d17954557216c43e inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return an unique id for this model (SACMODEL_PLANE). <br /></td></tr>
<tr class="separator:aec6058c4d1e3e467d17954557216c43e inherit pub_methods_classpcl_1_1_sample_consensus_model_plane"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_sample_consensus_model"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_sample_consensus_model')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model.html">pcl::SampleConsensusModel&lt; PointT &gt;</a></td></tr>
<tr class="memitem:aa99d99ea0457237eca3b2f8e9a39022b inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#aa99d99ea0457237eca3b2f8e9a39022b">SampleConsensusModel</a> (const PointCloudConstPtr &amp;cloud, bool random=false)</td></tr>
<tr class="memdesc:aa99d99ea0457237eca3b2f8e9a39022b inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model.html" title="SampleConsensusModel represents the base model class. All sample consensus models must inherit from t...">SampleConsensusModel</a>.  <a href="classpcl_1_1_sample_consensus_model.html#aa99d99ea0457237eca3b2f8e9a39022b">更多...</a><br /></td></tr>
<tr class="separator:aa99d99ea0457237eca3b2f8e9a39022b inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3fd6d364bc52a69c6aff54691975b7aa inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a3fd6d364bc52a69c6aff54691975b7aa">SampleConsensusModel</a> (const PointCloudConstPtr &amp;cloud, const std::vector&lt; int &gt; &amp;indices, bool random=false)</td></tr>
<tr class="memdesc:a3fd6d364bc52a69c6aff54691975b7aa inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model.html" title="SampleConsensusModel represents the base model class. All sample consensus models must inherit from t...">SampleConsensusModel</a>.  <a href="classpcl_1_1_sample_consensus_model.html#a3fd6d364bc52a69c6aff54691975b7aa">更多...</a><br /></td></tr>
<tr class="separator:a3fd6d364bc52a69c6aff54691975b7aa inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6fd82ae7fce7b90406608b8db249acd1 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a6fd82ae7fce7b90406608b8db249acd1"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a6fd82ae7fce7b90406608b8db249acd1">~SampleConsensusModel</a> ()</td></tr>
<tr class="memdesc:a6fd82ae7fce7b90406608b8db249acd1 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor for base <a class="el" href="classpcl_1_1_sample_consensus_model.html" title="SampleConsensusModel represents the base model class. All sample consensus models must inherit from t...">SampleConsensusModel</a>. <br /></td></tr>
<tr class="separator:a6fd82ae7fce7b90406608b8db249acd1 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2ae178816daf4f2c7af3a19d12324b77 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a2ae178816daf4f2c7af3a19d12324b77">getSamples</a> (int &amp;iterations, std::vector&lt; int &gt; &amp;samples)</td></tr>
<tr class="memdesc:a2ae178816daf4f2c7af3a19d12324b77 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a set of random data samples and return them as point indices.  <a href="classpcl_1_1_sample_consensus_model.html#a2ae178816daf4f2c7af3a19d12324b77">更多...</a><br /></td></tr>
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<tr class="memitem:aae3b06fbee5243f926d40f8115bd406c inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#aae3b06fbee5243f926d40f8115bd406c">setInputCloud</a> (const PointCloudConstPtr &amp;cloud)</td></tr>
<tr class="memdesc:aae3b06fbee5243f926d40f8115bd406c inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input dataset  <a href="classpcl_1_1_sample_consensus_model.html#aae3b06fbee5243f926d40f8115bd406c">更多...</a><br /></td></tr>
<tr class="separator:aae3b06fbee5243f926d40f8115bd406c inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a41226f6ed6de6db5ea190f265f520fc9 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a41226f6ed6de6db5ea190f265f520fc9"></a>
PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a41226f6ed6de6db5ea190f265f520fc9">getInputCloud</a> () const</td></tr>
<tr class="memdesc:a41226f6ed6de6db5ea190f265f520fc9 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the input point cloud dataset. <br /></td></tr>
<tr class="separator:a41226f6ed6de6db5ea190f265f520fc9 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4d9b6652b63eacd8c0ae1fb3a3eafa25 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a4d9b6652b63eacd8c0ae1fb3a3eafa25">setIndices</a> (const boost::shared_ptr&lt; std::vector&lt; int &gt; &gt; &amp;indices)</td></tr>
<tr class="memdesc:a4d9b6652b63eacd8c0ae1fb3a3eafa25 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the vector of indices that represents the input data.  <a href="classpcl_1_1_sample_consensus_model.html#a4d9b6652b63eacd8c0ae1fb3a3eafa25">更多...</a><br /></td></tr>
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<tr class="memitem:a6d23c173237ca4be1451182b9a84b3ac inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a6d23c173237ca4be1451182b9a84b3ac">setIndices</a> (const std::vector&lt; int &gt; &amp;indices)</td></tr>
<tr class="memdesc:a6d23c173237ca4be1451182b9a84b3ac inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide the vector of indices that represents the input data.  <a href="classpcl_1_1_sample_consensus_model.html#a6d23c173237ca4be1451182b9a84b3ac">更多...</a><br /></td></tr>
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<tr class="memitem:a7b59467495bbcc1e6ba1b69bbd6c4206 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a7b59467495bbcc1e6ba1b69bbd6c4206"></a>
boost::shared_ptr&lt; std::vector&lt; int &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a7b59467495bbcc1e6ba1b69bbd6c4206">getIndices</a> () const</td></tr>
<tr class="memdesc:a7b59467495bbcc1e6ba1b69bbd6c4206 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the vector of indices used. <br /></td></tr>
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<tr class="memitem:a490884cb22bfa92325111bd5be0bbe96 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a490884cb22bfa92325111bd5be0bbe96"></a>
const std::string &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a490884cb22bfa92325111bd5be0bbe96">getClassName</a> () const</td></tr>
<tr class="memdesc:a490884cb22bfa92325111bd5be0bbe96 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a string representation of the name of this class. <br /></td></tr>
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<tr class="memitem:aff175b4323080fe1a3ca98a76ca4da46 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="aff175b4323080fe1a3ca98a76ca4da46"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#aff175b4323080fe1a3ca98a76ca4da46">getSampleSize</a> () const</td></tr>
<tr class="memdesc:aff175b4323080fe1a3ca98a76ca4da46 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return the size of a sample from which the model is computed. <br /></td></tr>
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<tr class="memitem:a35884d269a39055c962b24d1db5fa97d inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a35884d269a39055c962b24d1db5fa97d"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a35884d269a39055c962b24d1db5fa97d">getModelSize</a> () const</td></tr>
<tr class="memdesc:a35884d269a39055c962b24d1db5fa97d inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return the number of coefficients in the model. <br /></td></tr>
<tr class="separator:a35884d269a39055c962b24d1db5fa97d inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3ed94271a12d7903c0bee9091e9a8f95 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a3ed94271a12d7903c0bee9091e9a8f95">setRadiusLimits</a> (const double &amp;min_radius, const double &amp;max_radius)</td></tr>
<tr class="memdesc:a3ed94271a12d7903c0bee9091e9a8f95 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate a radius)  <a href="classpcl_1_1_sample_consensus_model.html#a3ed94271a12d7903c0bee9091e9a8f95">更多...</a><br /></td></tr>
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<tr class="memitem:acff95be7097cf723a598d3b28e828487 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#acff95be7097cf723a598d3b28e828487">getRadiusLimits</a> (double &amp;min_radius, double &amp;max_radius)</td></tr>
<tr class="memdesc:acff95be7097cf723a598d3b28e828487 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the minimum and maximum allowable radius limits for the model as set by the user.  <a href="classpcl_1_1_sample_consensus_model.html#acff95be7097cf723a598d3b28e828487">更多...</a><br /></td></tr>
<tr class="separator:acff95be7097cf723a598d3b28e828487 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af9eea9dd0e12e1de8671ac542400d3f1 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#af9eea9dd0e12e1de8671ac542400d3f1">setSamplesMaxDist</a> (const double &amp;radius, SearchPtr search)</td></tr>
<tr class="memdesc:af9eea9dd0e12e1de8671ac542400d3f1 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the maximum distance allowed when drawing random samples  <a href="classpcl_1_1_sample_consensus_model.html#af9eea9dd0e12e1de8671ac542400d3f1">更多...</a><br /></td></tr>
<tr class="separator:af9eea9dd0e12e1de8671ac542400d3f1 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1aebacea0f2bdd7529f48f739f11c6c0 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a1aebacea0f2bdd7529f48f739f11c6c0">getSamplesMaxDist</a> (double &amp;radius)</td></tr>
<tr class="memdesc:a1aebacea0f2bdd7529f48f739f11c6c0 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get maximum distance allowed when drawing random samples  <a href="classpcl_1_1_sample_consensus_model.html#a1aebacea0f2bdd7529f48f739f11c6c0">更多...</a><br /></td></tr>
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<tr class="memitem:a2ac96856f60671f5d56be00a174963a8 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a2ac96856f60671f5d56be00a174963a8">computeVariance</a> (const std::vector&lt; double &gt; &amp;error_sqr_dists)</td></tr>
<tr class="memdesc:a2ac96856f60671f5d56be00a174963a8 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the variance of the errors to the model.  <a href="classpcl_1_1_sample_consensus_model.html#a2ac96856f60671f5d56be00a174963a8">更多...</a><br /></td></tr>
<tr class="separator:a2ac96856f60671f5d56be00a174963a8 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad3de5bb66de04a4f0b3bc014a0676d48 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="ad3de5bb66de04a4f0b3bc014a0676d48"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#ad3de5bb66de04a4f0b3bc014a0676d48">computeVariance</a> ()</td></tr>
<tr class="memdesc:ad3de5bb66de04a4f0b3bc014a0676d48 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Compute the variance of the errors to the model from the internally estimated vector of distances. The model must be computed first (or at least selectWithinDistance must be called). <br /></td></tr>
<tr class="separator:ad3de5bb66de04a4f0b3bc014a0676d48 inherit pub_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classpcl_1_1_sample_consensus_model_from_normals')"><img src="closed.png" alt="-"/>&#160;Public 成员函数 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">pcl::SampleConsensusModelFromNormals&lt; PointT, PointNT &gt;</a></td></tr>
<tr class="memitem:aac33c2093acaca505d27397c0cc0af71 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="aac33c2093acaca505d27397c0cc0af71"></a>
&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#aac33c2093acaca505d27397c0cc0af71">SampleConsensusModelFromNormals</a> ()</td></tr>
<tr class="memdesc:aac33c2093acaca505d27397c0cc0af71 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html" title="SampleConsensusModelFromNormals represents the base model class for models that require the use of su...">SampleConsensusModelFromNormals</a>. <br /></td></tr>
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<tr class="memitem:a010f51999fde7c867ea2a6b53a7887b8 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="a010f51999fde7c867ea2a6b53a7887b8"></a>
virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#a010f51999fde7c867ea2a6b53a7887b8">~SampleConsensusModelFromNormals</a> ()</td></tr>
<tr class="memdesc:a010f51999fde7c867ea2a6b53a7887b8 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <br /></td></tr>
<tr class="separator:a010f51999fde7c867ea2a6b53a7887b8 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a490b2a89f60d8fafa2c7fd6b8f761c85 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#a490b2a89f60d8fafa2c7fd6b8f761c85">setNormalDistanceWeight</a> (const double w)</td></tr>
<tr class="memdesc:a490b2a89f60d8fafa2c7fd6b8f761c85 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the normal angular distance weight.  <a href="classpcl_1_1_sample_consensus_model_from_normals.html#a490b2a89f60d8fafa2c7fd6b8f761c85">更多...</a><br /></td></tr>
<tr class="separator:a490b2a89f60d8fafa2c7fd6b8f761c85 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3d5c831e4e7469f3b2e30ab9cad559b3 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="a3d5c831e4e7469f3b2e30ab9cad559b3"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#a3d5c831e4e7469f3b2e30ab9cad559b3">getNormalDistanceWeight</a> ()</td></tr>
<tr class="memdesc:a3d5c831e4e7469f3b2e30ab9cad559b3 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get the normal angular distance weight. <br /></td></tr>
<tr class="separator:a3d5c831e4e7469f3b2e30ab9cad559b3 inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8945c93d6a5f7b436b527794888ec1be inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#a8945c93d6a5f7b436b527794888ec1be">setInputNormals</a> (const PointCloudNConstPtr &amp;normals)</td></tr>
<tr class="memdesc:a8945c93d6a5f7b436b527794888ec1be inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.  <a href="classpcl_1_1_sample_consensus_model_from_normals.html#a8945c93d6a5f7b436b527794888ec1be">更多...</a><br /></td></tr>
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<tr class="memitem:af878ad2a4bb4badec569eb51d94d5a0d inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="af878ad2a4bb4badec569eb51d94d5a0d"></a>
PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#af878ad2a4bb4badec569eb51d94d5a0d">getInputNormals</a> ()</td></tr>
<tr class="memdesc:af878ad2a4bb4badec569eb51d94d5a0d inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">Get a pointer to the normals of the input XYZ point cloud dataset. <br /></td></tr>
<tr class="separator:af878ad2a4bb4badec569eb51d94d5a0d inherit pub_methods_classpcl_1_1_sample_consensus_model_from_normals"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
额外继承的成员函数</h2></td></tr>
<tr class="inherit_header pro_methods_classpcl_1_1_sample_consensus_model"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classpcl_1_1_sample_consensus_model')"><img src="closed.png" alt="-"/>&#160;Protected 成员函数 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model.html">pcl::SampleConsensusModel&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a910f3f0d75a6c2bf8bc4a9c43df825ce inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a910f3f0d75a6c2bf8bc4a9c43df825ce">SampleConsensusModel</a> (bool random=false)</td></tr>
<tr class="memdesc:a910f3f0d75a6c2bf8bc4a9c43df825ce inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Empty constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model.html" title="SampleConsensusModel represents the base model class. All sample consensus models must inherit from t...">SampleConsensusModel</a>.  <a href="classpcl_1_1_sample_consensus_model.html#a910f3f0d75a6c2bf8bc4a9c43df825ce">更多...</a><br /></td></tr>
<tr class="separator:a910f3f0d75a6c2bf8bc4a9c43df825ce inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2f687798633c8e702568aea8d68b2bec inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a2f687798633c8e702568aea8d68b2bec">drawIndexSample</a> (std::vector&lt; int &gt; &amp;sample)</td></tr>
<tr class="memdesc:a2f687798633c8e702568aea8d68b2bec inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fills a sample array with random samples from the indices_ vector  <a href="classpcl_1_1_sample_consensus_model.html#a2f687798633c8e702568aea8d68b2bec">更多...</a><br /></td></tr>
<tr class="separator:a2f687798633c8e702568aea8d68b2bec inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a94696e418be704a4443b031ca18bc298 inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a94696e418be704a4443b031ca18bc298">drawIndexSampleRadius</a> (std::vector&lt; int &gt; &amp;sample)</td></tr>
<tr class="memdesc:a94696e418be704a4443b031ca18bc298 inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Fills a sample array with one random sample from the indices_ vector and other random samples that are closer than samples_radius_  <a href="classpcl_1_1_sample_consensus_model.html#a94696e418be704a4443b031ca18bc298">更多...</a><br /></td></tr>
<tr class="separator:a94696e418be704a4443b031ca18bc298 inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad22a9cfdd9cf08bcf85ef1e88b62b9d2 inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">virtual bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#ad22a9cfdd9cf08bcf85ef1e88b62b9d2">isModelValid</a> (const Eigen::VectorXf &amp;model_coefficients)</td></tr>
<tr class="memdesc:ad22a9cfdd9cf08bcf85ef1e88b62b9d2 inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check whether a model is valid given the user constraints.  <a href="classpcl_1_1_sample_consensus_model.html#ad22a9cfdd9cf08bcf85ef1e88b62b9d2">更多...</a><br /></td></tr>
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int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#ab8b77e6a4edb210c2ddaca923ac8470a">rnd</a> ()</td></tr>
<tr class="memdesc:ab8b77e6a4edb210c2ddaca923ac8470a inherit pro_methods_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Boost-based random number generator. <br /></td></tr>
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<tr class="inherit_header pro_attribs_classpcl_1_1_sample_consensus_model"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_sample_consensus_model')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model.html">pcl::SampleConsensusModel&lt; PointT &gt;</a></td></tr>
<tr class="memitem:ab10fd6af7c7ab78040d4f638a572943f inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="ab10fd6af7c7ab78040d4f638a572943f"></a>
std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#ab10fd6af7c7ab78040d4f638a572943f">model_name_</a></td></tr>
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PointCloudConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a7bffa6777a49f1c461ee8e0960bbec01">input_</a></td></tr>
<tr class="memdesc:a7bffa6777a49f1c461ee8e0960bbec01 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">A boost shared pointer to the point cloud data array. <br /></td></tr>
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boost::shared_ptr&lt; std::vector&lt; int &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a></td></tr>
<tr class="memdesc:ad45adf0e36f396a908c2ba08cfdd7a41 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the vector of point indices to use. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a3e4708339fa0bc73aac513ddb1891a18">radius_min_</a></td></tr>
<tr class="memdesc:a3e4708339fa0bc73aac513ddb1891a18 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">The minimum and maximum radius limits for the model. Applicable to all models that estimate a radius. <br /></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><b>radius_max_</b></td></tr>
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double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#aab89218101a313d2aa8adcaf6991f73b">samples_radius_</a></td></tr>
<tr class="memdesc:aab89218101a313d2aa8adcaf6991f73b inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">The maximum distance of subsequent samples from the first (radius search) <br /></td></tr>
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SearchPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a4b939f4747b5d6e12b03148a680380c3">samples_radius_search_</a></td></tr>
<tr class="memdesc:a4b939f4747b5d6e12b03148a680380c3 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">The search object for picking subsequent samples using radius search <br /></td></tr>
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boost::mt19937&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a73e9fb74bbe6ba122781c42913618756">rng_alg_</a></td></tr>
<tr class="memdesc:a73e9fb74bbe6ba122781c42913618756 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Boost-based random number generator algorithm. <br /></td></tr>
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boost::shared_ptr&lt; boost::uniform_int&lt;&gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a81041dab94f5b0a5644697a12c4b9351">rng_dist_</a></td></tr>
<tr class="memdesc:a81041dab94f5b0a5644697a12c4b9351 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Boost-based random number generator distribution. <br /></td></tr>
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<tr class="memitem:a7c57e94b06912d8bbf472667ba9940db inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a7c57e94b06912d8bbf472667ba9940db"></a>
boost::shared_ptr&lt; boost::variate_generator&lt; boost::mt19937 &amp;, boost::uniform_int&lt;&gt; &gt; &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a7c57e94b06912d8bbf472667ba9940db">rng_gen_</a></td></tr>
<tr class="memdesc:a7c57e94b06912d8bbf472667ba9940db inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">Boost-based random number generator. <br /></td></tr>
<tr class="separator:a7c57e94b06912d8bbf472667ba9940db inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af526982856012edcfa78ffc0fd589f97 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="af526982856012edcfa78ffc0fd589f97"></a>
std::vector&lt; double &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#af526982856012edcfa78ffc0fd589f97">error_sqr_dists_</a></td></tr>
<tr class="memdesc:af526982856012edcfa78ffc0fd589f97 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">A vector holding the distances to the computed model. Used internally. <br /></td></tr>
<tr class="separator:af526982856012edcfa78ffc0fd589f97 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a64854cad238a0583093c446dc295f245 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="a64854cad238a0583093c446dc295f245"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a64854cad238a0583093c446dc295f245">sample_size_</a></td></tr>
<tr class="memdesc:a64854cad238a0583093c446dc295f245 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">The size of a sample from which the model is computed. Every subclass should initialize this appropriately. <br /></td></tr>
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<tr class="memitem:ab7f51bf1c63fcfb05694d0f19c2f7dc3 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top"><a id="ab7f51bf1c63fcfb05694d0f19c2f7dc3"></a>
unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#ab7f51bf1c63fcfb05694d0f19c2f7dc3">model_size_</a></td></tr>
<tr class="memdesc:ab7f51bf1c63fcfb05694d0f19c2f7dc3 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="mdescLeft">&#160;</td><td class="mdescRight">The number of coefficients in the model. Every subclass should initialize this appropriately. <br /></td></tr>
<tr class="separator:ab7f51bf1c63fcfb05694d0f19c2f7dc3 inherit pro_attribs_classpcl_1_1_sample_consensus_model"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classpcl_1_1_sample_consensus_model_from_normals')"><img src="closed.png" alt="-"/>&#160;Protected 属性 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html">pcl::SampleConsensusModelFromNormals&lt; PointT, PointNT &gt;</a></td></tr>
<tr class="memitem:ae21dd06dfc1c624f72925edff6c882e4 inherit pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="ae21dd06dfc1c624f72925edff6c882e4"></a>
double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#ae21dd06dfc1c624f72925edff6c882e4">normal_distance_weight_</a></td></tr>
<tr class="memdesc:ae21dd06dfc1c624f72925edff6c882e4 inherit pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point normals and the plane normal. <br /></td></tr>
<tr class="separator:ae21dd06dfc1c624f72925edff6c882e4 inherit pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5518bb7163a19fbc4a79d76f03742c0b inherit pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td class="memItemLeft" align="right" valign="top"><a id="a5518bb7163a19fbc4a79d76f03742c0b"></a>
PointCloudNConstPtr&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a></td></tr>
<tr class="memdesc:a5518bb7163a19fbc4a79d76f03742c0b inherit pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td class="mdescLeft">&#160;</td><td class="mdescRight">A pointer to the input dataset that contains the point normals of the XYZ dataset. <br /></td></tr>
<tr class="separator:a5518bb7163a19fbc4a79d76f03742c0b inherit pro_attribs_classpcl_1_1_sample_consensus_model_from_normals"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_static_attribs_classpcl_1_1_sample_consensus_model"><td colspan="2" onclick="javascript:toggleInherit('pro_static_attribs_classpcl_1_1_sample_consensus_model')"><img src="closed.png" alt="-"/>&#160;静态 Protected 属性 继承自 <a class="el" href="classpcl_1_1_sample_consensus_model.html">pcl::SampleConsensusModel&lt; PointT &gt;</a></td></tr>
<tr class="memitem:a19d4a467b5c0cd6267e6282ac0a2cf8c inherit pro_static_attribs_classpcl_1_1_sample_consensus_model"><td class="memItemLeft" align="right" valign="top">static const unsigned int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classpcl_1_1_sample_consensus_model.html#a19d4a467b5c0cd6267e6282ac0a2cf8c">max_sample_checks_</a> = 1000</td></tr>
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</table>
<a name="details" id="details"></a><h2 class="groupheader">详细描述</h2>
<div class="textblock"><h3>template&lt;typename PointT, typename PointNT&gt;<br />
class pcl::SampleConsensusModelNormalPlane&lt; PointT, PointNT &gt;</h3>

<p><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html" title="SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface no...">SampleConsensusModelNormalPlane</a> defines a model for 3D plane segmentation using additional surface normal constraints. Basically this means that checking for inliers will not only involve a "distance to
model" criterion, but also an additional "maximum angular deviation" between the plane's normal and the inlier points normals. </p>
<p>The model coefficients are defined as:</p><ul>
<li><b>a</b> : the X coordinate of the plane's normal (normalized)</li>
<li><b>b</b> : the Y coordinate of the plane's normal (normalized)</li>
<li><b>c</b> : the Z coordinate of the plane's normal (normalized)</li>
<li><b>d</b> : the fourth <a href="http://mathworld.wolfram.com/HessianNormalForm.html">Hessian component</a> of the plane's equation</li>
</ul>
<p>To set the influence of the surface normals in the inlier estimation process, set the normal weight (0.0-1.0), e.g.: </p><div class="fragment"><div class="line">SampleConsensusModelNormalPlane&lt;pcl::PointXYZ, pcl::Normal&gt; sac_model;</div>
<div class="line">...</div>
<div class="line">sac_model.setNormalDistanceWeight (0.1);</div>
<div class="line">...</div>
</div><!-- fragment --><dl class="section author"><dt>作者</dt><dd>Radu B. Rusu and Jared Glover </dd></dl>
</div><h2 class="groupheader">构造及析构函数说明</h2>
<a id="a6057b518b385f7cb814a21f0e624069d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a6057b518b385f7cb814a21f0e624069d">&#9670;&nbsp;</a></span>SampleConsensusModelNormalPlane() <span class="overload">[1/2]</span></h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">pcl::SampleConsensusModelNormalPlane</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::<a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">SampleConsensusModelNormalPlane</a> </td>
          <td>(</td>
          <td class="paramtype">const PointCloudConstPtr &amp;&#160;</td>
          <td class="paramname"><em>cloud</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>random</em> = <code>false</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
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<p>Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html" title="SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface no...">SampleConsensusModelNormalPlane</a>. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">cloud</td><td>the input point cloud dataset </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">random</td><td>if true set the random seed to the current time, else set to 12345 (default: false) </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        : SampleConsensusModelPlane&lt;PointT&gt; (cloud, random)</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        , SampleConsensusModelFromNormals&lt;PointT, PointNT&gt; ()</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;      {</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        <a class="code" href="classpcl_1_1_sample_consensus_model.html#ab10fd6af7c7ab78040d4f638a572943f">model_name_</a> = <span class="stringliteral">&quot;SampleConsensusModelNormalPlane&quot;</span>;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        <a class="code" href="classpcl_1_1_sample_consensus_model.html#a64854cad238a0583093c446dc295f245">sample_size_</a> = 3;</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;        <a class="code" href="classpcl_1_1_sample_consensus_model.html#ab7f51bf1c63fcfb05694d0f19c2f7dc3">model_size_</a> = 4;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;      }</div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_a64854cad238a0583093c446dc295f245"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#a64854cad238a0583093c446dc295f245">pcl::SampleConsensusModel::sample_size_</a></div><div class="ttdeci">unsigned int sample_size_</div><div class="ttdoc">The size of a sample from which the model is computed. Every subclass should initialize this appropri...</div><div class="ttdef"><b>Definition:</b> sac_model.h:572</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_ab10fd6af7c7ab78040d4f638a572943f"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#ab10fd6af7c7ab78040d4f638a572943f">pcl::SampleConsensusModel::model_name_</a></div><div class="ttdeci">std::string model_name_</div><div class="ttdoc">The model name.</div><div class="ttdef"><b>Definition:</b> sac_model.h:534</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_ab7f51bf1c63fcfb05694d0f19c2f7dc3"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#ab7f51bf1c63fcfb05694d0f19c2f7dc3">pcl::SampleConsensusModel::model_size_</a></div><div class="ttdeci">unsigned int model_size_</div><div class="ttdoc">The number of coefficients in the model. Every subclass should initialize this appropriately.</div><div class="ttdef"><b>Definition:</b> sac_model.h:575</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#ab86a5b9c29702bf097861986d9ea67bf">&#9670;&nbsp;</a></span>SampleConsensusModelNormalPlane() <span class="overload">[2/2]</span></h2>

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template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname"><a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">pcl::SampleConsensusModelNormalPlane</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::<a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">SampleConsensusModelNormalPlane</a> </td>
          <td>(</td>
          <td class="paramtype">const PointCloudConstPtr &amp;&#160;</td>
          <td class="paramname"><em>cloud</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const std::vector&lt; int &gt; &amp;&#160;</td>
          <td class="paramname"><em>indices</em>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>random</em> = <code>false</code>&#160;</td>
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          <td>)</td>
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<p>Constructor for base <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html" title="SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface no...">SampleConsensusModelNormalPlane</a>. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">cloud</td><td>the input point cloud dataset </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">indices</td><td>a vector of point indices to be used from <em>cloud</em> </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">random</td><td>if true set the random seed to the current time, else set to 12345 (default: false) </td></tr>
  </table>
  </dd>
</dl>
<div class="fragment"><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        : SampleConsensusModelPlane&lt;PointT&gt; (cloud, indices, random)</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;        , SampleConsensusModelFromNormals&lt;PointT, PointNT&gt; ()</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;      {</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;        <a class="code" href="classpcl_1_1_sample_consensus_model.html#ab10fd6af7c7ab78040d4f638a572943f">model_name_</a> = <span class="stringliteral">&quot;SampleConsensusModelNormalPlane&quot;</span>;</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        <a class="code" href="classpcl_1_1_sample_consensus_model.html#a64854cad238a0583093c446dc295f245">sample_size_</a> = 3;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;        <a class="code" href="classpcl_1_1_sample_consensus_model.html#ab7f51bf1c63fcfb05694d0f19c2f7dc3">model_size_</a> = 4;</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;      }</div>
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<h2 class="groupheader">成员函数说明</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a97823e42845ee811261d929ecc272005">&#9670;&nbsp;</a></span>countWithinDistance()</h2>

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template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname">int <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">pcl::SampleConsensusModelNormalPlane</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::countWithinDistance </td>
          <td>(</td>
          <td class="paramtype">const Eigen::VectorXf &amp;&#160;</td>
          <td class="paramname"><em>model_coefficients</em>, </td>
        </tr>
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          <td></td>
          <td class="paramtype">const double&#160;</td>
          <td class="paramname"><em>threshold</em>&#160;</td>
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          <td>)</td>
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<p>Count all the points which respect the given model coefficients as inliers. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">model_coefficients</td><td>the coefficients of a model that we need to compute distances to </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">threshold</td><td>maximum admissible distance threshold for determining the inliers from the outliers </td></tr>
  </table>
  </dd>
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<dl class="section return"><dt>返回</dt><dd>the resultant number of inliers </dd></dl>

<p>重载 <a class="el" href="classpcl_1_1_sample_consensus_model_plane.html#a31f725415cba23e71d95e4fa9c70b7f9">pcl::SampleConsensusModelPlane&lt; PointT &gt;</a> .</p>
<div class="fragment"><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;{</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a>)</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;  {</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::SampleConsensusModelNormalPlane::countWithinDistance] No input dataset containing normals was given!\n&quot;</span>);</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="keywordflow">return</span> (0);</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  }</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160; </div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;  <span class="comment">// Check if the model is valid given the user constraints</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_sample_consensus_model.html#ad22a9cfdd9cf08bcf85ef1e88b62b9d2">isModelValid</a> (model_coefficients))</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keywordflow">return</span> (0);</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160; </div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;  <span class="comment">// Obtain the plane normal</span></div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;  Eigen::Vector4f coeff = model_coefficients;</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  coeff[3] = 0;</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160; </div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  <span class="keywordtype">int</span> nr_p = 0;</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the plane</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; <a class="code" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a>-&gt;size (); ++i)</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  {</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>  &amp;pt = <a class="code" href="classpcl_1_1_sample_consensus_model.html#a7bffa6777a49f1c461ee8e0960bbec01">input_</a>-&gt;points[(*indices_)[i]];</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    <span class="keyword">const</span> PointNT &amp;nt = <a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a>-&gt;points[(*indices_)[i]];</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="comment">// Calculate the distance from the point to the plane normal as the dot product</span></div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="comment">// D = (P-A).N/|N|</span></div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    Eigen::Vector4f p (pt.x, pt.y, pt.z, 0);</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    Eigen::Vector4f n (nt.normal_x, nt.normal_y, nt.normal_z, 0);</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="keywordtype">double</span> d_euclid = fabs (coeff.dot (p) + model_coefficients[3]);</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160; </div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    <span class="comment">// Calculate the angular distance between the point normal and the plane normal</span></div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    <span class="keywordtype">double</span> d_normal = fabs (<a class="code" href="group__common.html#ga54999c02ba9bee56404539747b0fda51">getAngle3D</a> (n, coeff));</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    d_normal = (std::min) (d_normal, M_PI - d_normal);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;    <span class="comment">// Weight with the point curvature. On flat surfaces, curvature -&gt; 0, which means the normal will have a higher influence</span></div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <span class="keywordtype">double</span> weight = <a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#ae21dd06dfc1c624f72925edff6c882e4">normal_distance_weight_</a> * (1.0 - nt.curvature);</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160; </div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    <span class="keywordflow">if</span> (fabs (weight * d_normal + (1.0 - weight) * d_euclid) &lt; threshold)</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;      nr_p++;</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;  }</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;  <span class="keywordflow">return</span> (nr_p);</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_from_normals_html_a5518bb7163a19fbc4a79d76f03742c0b"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">pcl::SampleConsensusModelFromNormals::normals_</a></div><div class="ttdeci">PointCloudNConstPtr normals_</div><div class="ttdoc">A pointer to the input dataset that contains the point normals of the XYZ dataset.</div><div class="ttdef"><b>Definition:</b> sac_model.h:645</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_from_normals_html_ae21dd06dfc1c624f72925edff6c882e4"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_from_normals.html#ae21dd06dfc1c624f72925edff6c882e4">pcl::SampleConsensusModelFromNormals::normal_distance_weight_</a></div><div class="ttdeci">double normal_distance_weight_</div><div class="ttdoc">The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point norma...</div><div class="ttdef"><b>Definition:</b> sac_model.h:640</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_a7bffa6777a49f1c461ee8e0960bbec01"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#a7bffa6777a49f1c461ee8e0960bbec01">pcl::SampleConsensusModel::input_</a></div><div class="ttdeci">PointCloudConstPtr input_</div><div class="ttdoc">A boost shared pointer to the point cloud data array.</div><div class="ttdef"><b>Definition:</b> sac_model.h:537</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_ad22a9cfdd9cf08bcf85ef1e88b62b9d2"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#ad22a9cfdd9cf08bcf85ef1e88b62b9d2">pcl::SampleConsensusModel::isModelValid</a></div><div class="ttdeci">virtual bool isModelValid(const Eigen::VectorXf &amp;model_coefficients)</div><div class="ttdoc">Check whether a model is valid given the user constraints.</div><div class="ttdef"><b>Definition:</b> sac_model.h:516</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_ad45adf0e36f396a908c2ba08cfdd7a41"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">pcl::SampleConsensusModel::indices_</a></div><div class="ttdeci">boost::shared_ptr&lt; std::vector&lt; int &gt; &gt; indices_</div><div class="ttdoc">A pointer to the vector of point indices to use.</div><div class="ttdef"><b>Definition:</b> sac_model.h:540</div></div>
<div class="ttc" id="agroup__common_html_ga54999c02ba9bee56404539747b0fda51"><div class="ttname"><a href="group__common.html#ga54999c02ba9bee56404539747b0fda51">pcl::getAngle3D</a></div><div class="ttdeci">double getAngle3D(const Eigen::Vector4f &amp;v1, const Eigen::Vector4f &amp;v2, const bool in_degree=false)</div><div class="ttdoc">Compute the smallest angle between two 3D vectors in radians (default) or degree.</div><div class="ttdef"><b>Definition:</b> common.hpp:46</div></div>
<div class="ttc" id="astructpcl_1_1_point_x_y_z_r_g_b_a_html"><div class="ttname"><a href="structpcl_1_1_point_x_y_z_r_g_b_a.html">pcl::PointXYZRGBA</a></div><div class="ttdoc">A point structure representing Euclidean xyz coordinates, and the RGBA color.</div><div class="ttdef"><b>Definition:</b> point_types.hpp:540</div></div>
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<h2 class="memtitle"><span class="permalink"><a href="#ad084c665f423e894bd4531c02f38c5a0">&#9670;&nbsp;</a></span>getDistancesToModel()</h2>

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<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
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          <td class="memname">void <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">pcl::SampleConsensusModelNormalPlane</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::getDistancesToModel </td>
          <td>(</td>
          <td class="paramtype">const Eigen::VectorXf &amp;&#160;</td>
          <td class="paramname"><em>model_coefficients</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; double &gt; &amp;&#160;</td>
          <td class="paramname"><em>distances</em>&#160;</td>
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        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
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<span class="mlabels"><span class="mlabel">virtual</span></span>  </td>
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<p>Compute all distances from the cloud data to a given plane model. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">model_coefficients</td><td>the coefficients of a plane model that we need to compute distances to </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">distances</td><td>the resultant estimated distances </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_sample_consensus_model.html#adc4ab752a4819218988ff5429b5a3c06">pcl::SampleConsensusModel&lt; PointT &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;{</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a>)</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  {</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::SampleConsensusModelNormalPlane::getDistancesToModel] No input dataset containing normals was given!\n&quot;</span>);</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;  }</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160; </div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  <span class="comment">// Check if the model is valid given the user constraints</span></div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_sample_consensus_model.html#ad22a9cfdd9cf08bcf85ef1e88b62b9d2">isModelValid</a> (model_coefficients))</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;  {</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    distances.clear ();</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  }</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160; </div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;  <span class="comment">// Obtain the plane normal</span></div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  Eigen::Vector4f coeff = model_coefficients;</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;  coeff[3] = 0;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160; </div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  distances.resize (<a class="code" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the plane</span></div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; <a class="code" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a>-&gt;size (); ++i)</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;  {</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>  &amp;pt = <a class="code" href="classpcl_1_1_sample_consensus_model.html#a7bffa6777a49f1c461ee8e0960bbec01">input_</a>-&gt;points[(*indices_)[i]];</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;    <span class="keyword">const</span> PointNT &amp;nt = <a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a>-&gt;points[(*indices_)[i]];</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <span class="comment">// Calculate the distance from the point to the plane normal as the dot product</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    <span class="comment">// D = (P-A).N/|N|</span></div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;    Eigen::Vector4f p (pt.x, pt.y, pt.z, 0);</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    Eigen::Vector4f n (nt.normal_x, nt.normal_y, nt.normal_z, 0);</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    <span class="keywordtype">double</span> d_euclid = fabs (coeff.dot (p) + model_coefficients[3]);</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160; </div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    <span class="comment">// Calculate the angular distance between the point normal and the plane normal</span></div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="keywordtype">double</span> d_normal = fabs (<a class="code" href="group__common.html#ga54999c02ba9bee56404539747b0fda51">getAngle3D</a> (n, coeff));</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    d_normal = (std::min) (d_normal, M_PI - d_normal);</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160; </div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    <span class="comment">// Weight with the point curvature. On flat surfaces, curvature -&gt; 0, which means the normal will have a higher influence</span></div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="keywordtype">double</span> weight = <a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#ae21dd06dfc1c624f72925edff6c882e4">normal_distance_weight_</a> * (1.0 - nt.curvature);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160; </div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    distances[i] = fabs (weight * d_normal + (1.0 - weight) * d_euclid);</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;  }</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;}</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a63bbd86abcfc9a3ac2572d7d4566cd35">&#9670;&nbsp;</a></span>selectWithinDistance()</h2>

<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename PointT , typename PointNT &gt; </div>
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">void <a class="el" href="classpcl_1_1_sample_consensus_model_normal_plane.html">pcl::SampleConsensusModelNormalPlane</a>&lt; <a class="el" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>, PointNT &gt;::selectWithinDistance </td>
          <td>(</td>
          <td class="paramtype">const Eigen::VectorXf &amp;&#160;</td>
          <td class="paramname"><em>model_coefficients</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const double&#160;</td>
          <td class="paramname"><em>threshold</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">std::vector&lt; int &gt; &amp;&#160;</td>
          <td class="paramname"><em>inliers</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">virtual</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Select all the points which respect the given model coefficients as inliers. </p>
<dl class="params"><dt>参数</dt><dd>
  <table class="params">
    <tr><td class="paramdir">[in]</td><td class="paramname">model_coefficients</td><td>the coefficients of a plane model that we need to compute distances to </td></tr>
    <tr><td class="paramdir">[in]</td><td class="paramname">threshold</td><td>a maximum admissible distance threshold for determining the inliers from the outliers </td></tr>
    <tr><td class="paramdir">[out]</td><td class="paramname">inliers</td><td>the resultant model inliers </td></tr>
  </table>
  </dd>
</dl>

<p>实现了 <a class="el" href="classpcl_1_1_sample_consensus_model.html#af9aefc3c3ab13ede1430c680e9243d26">pcl::SampleConsensusModel&lt; PointT &gt;</a>.</p>
<div class="fragment"><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;{</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a>)</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  {</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::SampleConsensusModelNormalPlane::selectWithinDistance] No input dataset containing normals was given!\n&quot;</span>);</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    inliers.clear ();</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;  }</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160; </div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  <span class="comment">// Check if the model is valid given the user constraints</span></div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;  <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_sample_consensus_model.html#ad22a9cfdd9cf08bcf85ef1e88b62b9d2">isModelValid</a> (model_coefficients))</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  {</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    inliers.clear ();</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  }</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160; </div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="comment">// Obtain the plane normal</span></div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  Eigen::Vector4f coeff = model_coefficients;</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  coeff[3] = 0;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160; </div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  <span class="keywordtype">int</span> nr_p = 0;</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  inliers.resize (<a class="code" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  <a class="code" href="classpcl_1_1_sample_consensus_model.html#af526982856012edcfa78ffc0fd589f97">error_sqr_dists_</a>.resize (<a class="code" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160; </div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the plane</span></div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; <a class="code" href="classpcl_1_1_sample_consensus_model.html#ad45adf0e36f396a908c2ba08cfdd7a41">indices_</a>-&gt;size (); ++i)</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  {</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a>  &amp;pt = <a class="code" href="classpcl_1_1_sample_consensus_model.html#a7bffa6777a49f1c461ee8e0960bbec01">input_</a>-&gt;points[(*indices_)[i]];</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    <span class="keyword">const</span> PointNT &amp;nt = <a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#a5518bb7163a19fbc4a79d76f03742c0b">normals_</a>-&gt;points[(*indices_)[i]];</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="comment">// Calculate the distance from the point to the plane normal as the dot product</span></div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    <span class="comment">// D = (P-A).N/|N|</span></div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    Eigen::Vector4f p (pt.x, pt.y, pt.z, 0);</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    Eigen::Vector4f n (nt.normal_x, nt.normal_y, nt.normal_z, 0);</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="keywordtype">double</span> d_euclid = fabs (coeff.dot (p) + model_coefficients[3]);</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160; </div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <span class="comment">// Calculate the angular distance between the point normal and the plane normal</span></div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="keywordtype">double</span> d_normal = fabs (<a class="code" href="group__common.html#ga54999c02ba9bee56404539747b0fda51">getAngle3D</a> (n, coeff));</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    d_normal = (std::min) (d_normal, M_PI - d_normal);</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160; </div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <span class="comment">// Weight with the point curvature. On flat surfaces, curvature -&gt; 0, which means the normal will have a higher influence</span></div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    <span class="keywordtype">double</span> weight = <a class="code" href="classpcl_1_1_sample_consensus_model_from_normals.html#ae21dd06dfc1c624f72925edff6c882e4">normal_distance_weight_</a> * (1.0 - nt.curvature);</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="keywordtype">double</span> <a class="code" href="common_2include_2pcl_2common_2geometry_8h.html#a2fc89f0c26b7c7377fcd2851fa933b87">distance</a> = fabs (weight * d_normal + (1.0 - weight) * d_euclid); </div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keywordflow">if</span> (distance &lt; threshold)</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    {</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;      <span class="comment">// Returns the indices of the points whose distances are smaller than the threshold</span></div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;      inliers[nr_p] = (*indices_)[i];</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;      <a class="code" href="classpcl_1_1_sample_consensus_model.html#af526982856012edcfa78ffc0fd589f97">error_sqr_dists_</a>[nr_p] = <a class="code" href="common_2include_2pcl_2common_2geometry_8h.html#a2fc89f0c26b7c7377fcd2851fa933b87">distance</a>;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;      ++nr_p;</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    }</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  }</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  inliers.resize (nr_p);</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  <a class="code" href="classpcl_1_1_sample_consensus_model.html#af526982856012edcfa78ffc0fd589f97">error_sqr_dists_</a>.resize (nr_p);</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;}</div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_html_af526982856012edcfa78ffc0fd589f97"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model.html#af526982856012edcfa78ffc0fd589f97">pcl::SampleConsensusModel::error_sqr_dists_</a></div><div class="ttdeci">std::vector&lt; double &gt; error_sqr_dists_</div><div class="ttdoc">A vector holding the distances to the computed model. Used internally.</div><div class="ttdef"><b>Definition:</b> sac_model.h:569</div></div>
<div class="ttc" id="acommon_2include_2pcl_2common_2geometry_8h_html_a2fc89f0c26b7c7377fcd2851fa933b87"><div class="ttname"><a href="common_2include_2pcl_2common_2geometry_8h.html#a2fc89f0c26b7c7377fcd2851fa933b87">pcl::geometry::distance</a></div><div class="ttdeci">float distance(const PointT &amp;p1, const PointT &amp;p2)</div><div class="ttdef"><b>Definition:</b> geometry.h:60</div></div>
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